private boolean missingColliders(Graph graph) {
List<Triple> colliders = getUnshieldedCollidersFromGraph(graph);
Graph copy = new EdgeListGraphSingleConnections(graph);
new MeekRules().orientImplied(copy);
if (copy.existsDirectedCycle()) return true;
List<Triple> newColliders = getUnshieldedCollidersFromGraph(copy);
newColliders.removeAll(colliders);
if (!newColliders.isEmpty()) {
return true;
}
return false;
}
public void setParametersTemplate(String parametersTemplate) throws ParseException {
if (parametersTemplate == null) {
throw new NullPointerException();
}
// Test to make sure it's parsable.
ExpressionParser parser = new ExpressionParser();
Expression expression = parser.parseExpression(parametersTemplate);
List<String> parameterNames = parser.getParameters();
if (!parameterNames.isEmpty()) {
throw new IllegalArgumentException(
"Initial distribution for a parameter may not "
+ "contain parameters: "
+ expression.toString());
}
this.parametersTemplate = parametersTemplate;
}
////////////////////////////////////////////
// RFCI Algorithm 4.4 (Colombo et al, 2012)
// Orient colliders
////////////////////////////////////////////
private void ruleR0_RFCI(List<Node[]> rTuples) {
List<Node[]> lTuples = new ArrayList<Node[]>();
List<Node> nodes = graph.getNodes();
///////////////////////////////
// process tuples in rTuples
while (!rTuples.isEmpty()) {
Node[] thisTuple = rTuples.remove(0);
Node i = thisTuple[0];
Node j = thisTuple[1];
Node k = thisTuple[2];
final List<Node> nodes1 = getSepset(i, k);
if (nodes1 == null) continue;
List<Node> sepSet = new ArrayList<Node>(nodes1);
sepSet.remove(j);
boolean independent1 = false;
if (knowledge.noEdgeRequired(i.getName(), j.getName())) // if BK allows
{
try {
independent1 = independenceTest.isIndependent(i, j, sepSet);
} catch (Exception e) {
independent1 = true;
}
}
boolean independent2 = false;
if (knowledge.noEdgeRequired(j.getName(), k.getName())) // if BK allows
{
try {
independent2 = independenceTest.isIndependent(j, k, sepSet);
} catch (Exception e) {
independent2 = true;
}
}
if (!independent1 && !independent2) {
lTuples.add(thisTuple);
} else {
// set sepSets to minimal separating sets
if (independent1) {
setMinSepSet(sepSet, i, j);
graph.removeEdge(i, j);
}
if (independent2) {
setMinSepSet(sepSet, j, k);
graph.removeEdge(j, k);
}
// add new unshielded tuples to rTuples
for (Node thisNode : nodes) {
List<Node> adjacentNodes = graph.getAdjacentNodes(thisNode);
if (independent1) // <i, ., j>
{
if (adjacentNodes.contains(i) && adjacentNodes.contains(j)) {
Node[] newTuple = {i, thisNode, j};
rTuples.add(newTuple);
}
}
if (independent2) // <j, ., k>
{
if (adjacentNodes.contains(j) && adjacentNodes.contains(k)) {
Node[] newTuple = {j, thisNode, k};
rTuples.add(newTuple);
}
}
}
// remove tuples involving either (if independent1) <i, j>
// or (if independent2) <j, k> from rTuples
Iterator<Node[]> iter = rTuples.iterator();
while (iter.hasNext()) {
Node[] curTuple = iter.next();
if ((independent1 && (curTuple[1] == i) && ((curTuple[0] == j) || (curTuple[2] == j)))
|| (independent2 && (curTuple[1] == k) && ((curTuple[0] == j) || (curTuple[2] == j)))
|| (independent1 && (curTuple[1] == j) && ((curTuple[0] == i) || (curTuple[2] == i)))
|| (independent2
&& (curTuple[1] == j)
&& ((curTuple[0] == k) || (curTuple[2] == k)))) {
iter.remove();
}
}
// remove tuples involving either (if independent1) <i, j>
// or (if independent2) <j, k> from lTuples
iter = lTuples.iterator();
while (iter.hasNext()) {
Node[] curTuple = iter.next();
if ((independent1 && (curTuple[1] == i) && ((curTuple[0] == j) || (curTuple[2] == j)))
|| (independent2 && (curTuple[1] == k) && ((curTuple[0] == j) || (curTuple[2] == j)))
|| (independent1 && (curTuple[1] == j) && ((curTuple[0] == i) || (curTuple[2] == i)))
|| (independent2
&& (curTuple[1] == j)
&& ((curTuple[0] == k) || (curTuple[2] == k)))) {
iter.remove();
}
}
}
}
///////////////////////////////////////////////////////
// orient colliders (similar to original FCI ruleR0)
for (Node[] thisTuple : lTuples) {
Node i = thisTuple[0];
Node j = thisTuple[1];
Node k = thisTuple[2];
List<Node> sepset = getSepset(i, k);
if (sepset == null) {
continue;
}
if (!sepset.contains(j) && graph.isAdjacentTo(i, j) && graph.isAdjacentTo(j, k)) {
if (!isArrowpointAllowed(i, j)) {
continue;
}
if (!isArrowpointAllowed(k, j)) {
continue;
}
graph.setEndpoint(i, j, Endpoint.ARROW);
graph.setEndpoint(k, j, Endpoint.ARROW);
printWrongColliderMessage(i, j, k, "R0_RFCI");
}
}
}
// Finds clusters of size 4 or higher.
private Set<Set<Integer>> findPureClusters(
List<Integer> _variables, Map<Node, Set<Node>> adjacencies) {
// System.out.println("Original variables = " + variables);
Set<Set<Integer>> clusters = new HashSet<Set<Integer>>();
List<Integer> allVariables = new ArrayList<Integer>();
for (int i = 0; i < this.variables.size(); i++) allVariables.add(i);
VARIABLES:
while (!_variables.isEmpty()) {
if (_variables.size() < 4) break;
for (int x : _variables) {
Node nodeX = variables.get(x);
List<Node> adjX = new ArrayList<Node>(adjacencies.get(nodeX));
adjX.retainAll(variablesForIndices(new ArrayList<Integer>(_variables)));
for (Node node : new ArrayList<Node>(adjX)) {
if (adjacencies.get(node).size() < 3) {
adjX.remove(node);
}
}
if (adjX.size() < 3) {
continue;
}
ChoiceGenerator gen = new ChoiceGenerator(adjX.size(), 3);
int[] choice;
while ((choice = gen.next()) != null) {
Node nodeY = adjX.get(choice[0]);
Node nodeZ = adjX.get(choice[1]);
Node nodeW = adjX.get(choice[2]);
int y = variables.indexOf(nodeY);
int w = variables.indexOf(nodeW);
int z = variables.indexOf(nodeZ);
Set<Integer> cluster = quartet(x, y, z, w);
if (!clique(cluster, adjacencies)) {
continue;
}
// Note that purity needs to be assessed with respect to all of the variables in order to
// remove all latent-measure impurities between pairs of latents.
if (pure(cluster, allVariables)) {
// Collections.shuffle(_variables);
O:
for (int o : _variables) {
if (cluster.contains(o)) continue;
cluster.add(o);
List<Integer> _cluster = new ArrayList<Integer>(cluster);
if (!clique(cluster, adjacencies)) {
cluster.remove(o);
continue O;
}
// if (!allVariablesDependent(cluster)) {
// cluster.remove(o);
// continue O;
// }
ChoiceGenerator gen2 = new ChoiceGenerator(_cluster.size(), 4);
int[] choice2;
int count = 0;
while ((choice2 = gen2.next()) != null) {
int x2 = _cluster.get(choice2[0]);
int y2 = _cluster.get(choice2[1]);
int z2 = _cluster.get(choice2[2]);
int w2 = _cluster.get(choice2[3]);
Set<Integer> quartet = quartet(x2, y2, z2, w2);
// Optimizes for large clusters.
if (quartet.contains(o)) {
if (++count > 50) continue O;
}
if (quartet.contains(o) && !pure(quartet, allVariables)) {
cluster.remove(o);
continue O;
}
}
}
System.out.println(
"Cluster found: " + variablesForIndices(new ArrayList<Integer>(cluster)));
clusters.add(cluster);
_variables.removeAll(cluster);
continue VARIABLES;
}
}
}
break;
}
return clusters;
}